Medical, clinical systems generally run a great many complex processes, which must be modeled through linking a large number of computer-implemented applications.
The applications generally relate to completely different uses, for example the data acquisition or the post-processing of the detected image data and/or the generating of a report (reporting).
As a rule, complex medical tasks can be modeled with a sequence of partial tasks, wherein a partial task can be executed by different users or optionally also by users in different user roles. For example, a physician in the role of a reporter should be able to read and process different datasets than a medical-technical assistant in his/her role.
The following scenario is intended as example for a reporting task. A reporting task is generally initiated by issuing a message, a so-called “requested procedure” message. A patient is then examined in a first step, for example with the aid of an imaging process (MR, CT, ultrasound etc.) and the obtained data are subsequently stored. Normally, this step is performed by a medical technical assistant (MTA) on a first work station. Following the completion of the examination, the data are processed, possibly in dependence on a specific clinical issue, which may relate to a cardiology analysis, a perfusion, a colonoscopy, or a selection of parts of a dataset. For some medical applications, it is helpful if the detected medical image data are emphasized and/or marked with optional measures, wherein this task is generally performed by a so-called super MTA on a second work station. The resulting data are also stored. Following the completion of the two aforementioned preparatory processing steps, a radiologist in the role of clinical reporter can then analyze the obtained data and the already reprocessed datasets for the purpose of writing a report.
Different steps of a medical task can be carried out on different work stations, wherein these steps can furthermore be executed with a time delay. For example, a radiologist could wait until the evening to prepare reports of all cardiology analyses made during the day.
In the same way, it is possible to sequentially execute all steps of a medical task, wherein this direct execution of the individual steps can be of interest, in particular in emergency case scenarios. For an emergency case scenario, it is furthermore conceivable for a radiologist to realize all steps in order to save time.
The aforementioned example shows that from an information-technology point of view, it is no trivial task to interconnect the different applications and to execute these applications with the aid of different users at different work stations, as well as to provide the necessary resources, including the required datasets.
Until now, so-called stateless applications were generally used for this, for example web applications. It is characteristic for stateless applications that there is no provisioning of the processed data and the results achieved with the applications. For medical technical applications, which generally resort to comprehensive image datasets, the use of stateless applications is not advantageous. With stateless applications, the system performance gets worse for a user when loading comprehensive image data because of the longer waiting times.
Insular solutions were also frequently used in the past, so that one application was generally run independent of other applications. The steps taken so far have clear disadvantages and, in particular, result in the loss of performance during the daily operations.